Patent application title: ENCODING METHOD, AND DECODING METHOD
Inventors:
Yutaka Murakami (Osaka, JP)
Assignees:
PANASONIC CORPORATION
IPC8 Class: AH03M1323FI
USPC Class:
714786
Class name: Pulse or data error handling digital data error correction forward error correction by tree code (e.g., convolutional)
Publication date: 2013-11-07
Patent application number: 20130297993
Abstract:
An encoding method generates an encoded sequence by performing encoding
of a given coding rate according to a predetermined parity check matrix.
The predetermined parity check matrix is a first parity check matrix or a
second parity check matrix. The first parity check matrix corresponds to
a low-density parity check (LDPC) convolutional code using a plurality of
parity check polynomials. The second parity check matrix is generated by
performing at least one of row permutation and column permutation with
respect to the first parity check matrix. An eth parity check polynomial
that satisfies zero, of the LDPC convolutional code, is expressible by
using a predetermined mathematical formula.Claims:
1. An encoding method comprising generating an encoded sequence
comprising: n-1 information sequences denoted as X1 through
Xn-1; and a parity sequence denoted as P, by encoding the n-1
information sequences at a (n-1)/n coding rate according to a
predetermined parity check matrix having m×z rows and
n×m×z columns, n being an integer no less than two, m being
an integer no less than two, and z being a natural number, wherein the
predetermined parity check matrix is a first parity check matrix or a
second parity check matrix, the first parity check matrix corresponding
to a low-density parity check (LDPC) convolutional code using a plurality
of parity check polynomials, the second parity check matrix generated by
performing at least one of row permutation and column permutation with
respect to the first parity check matrix, and given e denoting an integer
no less than zero and no greater than m×z-1, α denoting an
integer no less than one and no greater than m×z, and i being a
variable denoting an integer that is no less than zero and no greater
than m-1 and satisfies i=e % m where % denotes a modulo operator, when
e≠α-1, an eth parity check polynomial that satisfies zero, of
the LDPC convolutional code, is expressed as ( D b 1 ,
i + 1 ) P ( D ) + k = 1 n - 1 { ( 1 +
j = 1 rk D ak , i , j ) X k ( D ) } = 0
( Math . 1 ) ##EQU00293## where b1,i is a natural number,
and when e=α-1, the eth parity check polynomial that satisfies
zero, of the LDPC convolutional code, is expressed as P ( D )
+ k = 1 n - 1 { ( 1 + j = 1 rk D ak ,
( α - 1 ) % m , j ) X k ( D ) } = 0
( Math . 2 ) ##EQU00294## where, in Math. 1 and Math. 2, p
denotes an integer no less than one and no greater than n-1, q denotes an
integer no less than one and no greater than rp, and rp denotes
an integer no less than three, D denotes a delay operator, Xp(D)
denotes a polynomial representation of an information sequence Xp
among the n-1 information sequences, and P(D) denotes a polynomial
representation of the parity sequence P, and ap,i,q denotes a
natural number, and when x and y are integers no less than one and no
greater than rp and satisfy x≠y, ap,i,x=ap,i,y holds
true for all x and y.
2. A decoding method comprising: generating an encoded sequence comprising: n-1 information sequences denoted as X1 through Xn-1; and a parity sequence denoted as P, by encoding the n-1 information sequences at a (n-1)/n coding rate according to a predetermined parity check matrix having m×z rows and n×m×z columns, n being an integer no less than two, m being an integer no less than two, and z being a natural number; and decoding the encoded sequence according to the predetermined parity check matrix by employing belief propagation (BP), wherein the predetermined parity check matrix is a first parity check matrix or a second parity check matrix, the first parity check matrix corresponding to a low-density parity check (LDPC) convolutional code using a plurality of parity check polynomials, the second parity check matrix generated by performing at least one of row permutation and column permutation with respect to the first parity check matrix, and given e denoting an integer no less than zero and no greater than m×z-1, a denoting an integer no less than one and no greater than m×z, and i being a variable denoting an integer that is no less than zero and no greater than m-1 and satisfies i=e % m where % denotes a modulo operator, when e≠a-1, an eth parity check polynomial that satisfies zero, of the LDPC convolutional code, is expressed as ( D b 1 , i + 1 ) P ( D ) + k = 1 n - 1 { ( 1 + j = 1 rk D ak , i , j ) X k ( D ) } = 0 ( Math . 1 ) ##EQU00295## where b1,i is a natural number, and when e=α-1, the eth parity check polynomial that satisfies zero, of the LDPC convolutional code, is expressed as P ( D ) + k = 1 n - 1 { ( 1 + j = 1 rk D ak , ( α - 1 ) % m , j ) X k ( D ) } = 0 ( Math . 2 ) ##EQU00296## where, in Math. 1 and Math. 2, p denotes an integer no less than one and no greater than n-1, q denotes an integer no less than one and no greater than rp, and rp denotes an integer no less than three, D denotes a delay operator, Xp(D) denotes a polynomial representation of an information sequence Xp among the n-1 information sequences, and P(D) denotes a polynomial representation of the parity sequence P, and ap,i,q denotes a natural number, and when x and y are integers no less than one and no greater than rp and satisfy x≠y, ap,i,x=ap,i,y holds true for all x and y.
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